scholarly journals The Relationship between Betatrophin Levels in Blood and T2DM: A Systematic Review and Meta-Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Song Yue ◽  
Jingyang Wu ◽  
Jiahua Zhang ◽  
Lei Liu ◽  
Lei Chen
Keyword(s):  
Diabetes Mellitus ◽  
Confidence Interval ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Caucasian Population ◽  
Effect Model ◽  
The Relationship ◽  
Strength Of Association

Background. In order to clarify previous ambiguous research conclusions, a meta-analysis was made to investigate the relationship between betatrophin levels in blood and type 2 diabetes mellitus (T2DM).Methods. We have searched all the English and Chinese references regarding the relationship between betatrophin and diabetes in database both manually and online. Strict criteria have been established to include and exclude articles, with Mean and Standard Deviation as statistics to evaluate strength of association. We have chosen either fixed- or random effect model according to heterogeneity inspection results and used Begg’s test and Egger’s test to analyze publication bias.Results. A total of 11 studies were included in this meta-analysis. Meta-analysis indicated a significant association between betatrophin and T2DM (Mean: 329.46; 95% confidence interval: 182.51 to 476.42,P<0.0001). However, in the subgroup analysis, there was no significant statistic between betatrophin concentration and T2DM within Caucasian population (Mean: 98.40; 95% confidence interval: −1585.08 to 1781.88,P=0.91).Conclusions. Such relationship may suggest preference for association between betatrophin and T2DM in different population.

scholarly journals Cyp2C19*2 Polymorphism Related to Clopidogrel Resistance in Patients With Coronary Heart Disease, Especially in the Asian Population: A Systematic Review and Meta-Analysis

2020 ◽  
Vol 11 ◽  
Author(s):  
Ying Sun ◽  
Qing Lu ◽  
Xuefei Tao ◽  
Biao Cheng ◽  
Guoxing Yang
Keyword(s):  
Gene Polymorphism ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Asian Population ◽  
Fixed Effect Model ◽  
Clopidogrel Resistance ◽  
Effect Model ◽  
The Relationship ◽  
Allele Model

In recent years, the relationship between Cyp2C19*2 gene polymorphism and clopidogrel resistance reflected by platelet function assay has been studied extensively, but there is no clear conclusion yet. In order to evaluate the relationship between Cyp2C19*2 gene polymorphism and clopidogrel resistance more accurately, meta-analysis was conducted in this study. The I2 value taking 50% as the limit, the heterogeneity is judged as high or low, and then a random effect model or a fixed effect model is selected for statistical analysis. PubMed, EMBASE, Web of Science, CNKI, and China Wanfang database were searched, and the related literatures from the establishment of the database to May 2020 were collected and analyzed by STATA 15.0 software. A total of 3,073 patients were involved in 12 studies, including 1,174 patients with clopidogrel resistance and 1,899 patients with non-clopidogrel resistance. The results of this study showed that allele model (A vs. G): OR = 2.42 (95%CI: 1.97–2.98); dominant model (AA+GA vs. GG): OR = 2.74 (95%CI: 2.09–3.59); recessive model (AA vs. GA+GG): OR = 4.07 (95%CI: 3.06–5.41); homozygous model (AA vs. GG): OR = 5.70 (95%CI: 4.22–7.71); heterozygote model (GA vs. GG): OR = 2.32 (95%CI: 1.76–3.07), the differences were statistically significant. Also, the analysis of the Ethnicity subgroup indicated that the Asian allele model and the other four gene models were statistically significant. In conclusion, Cyp2C19*2 gene polymorphism is strongly associated with clopidogrel resistance. Allele A, genotype GA, AA, and GG + GA can increase clopidogrel resistance, especially in the Asian population.

scholarly journals Association Between Lipoprotein (A) and Diabetic Nephropathy in Patients With Type 2 Diabetes Mellitus: A Meta-Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaoyan Ren ◽  
Zhihui Zhang ◽  
Zhaoli Yan
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Diabetic Nephropathy ◽  
Observational Studies ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Lipoprotein A

BackgroundLipoprotein (a) [Lp (a)] has been well recognized as a risk factor of cardiovascular disease. However, the association between serum Lp (a) and diabetic nephropathy in patients with type 2 diabetes mellitus (T2DM) remains unknown. We performed a meta-analysis to comprehensively evaluate the above association.MethodsObservational studies aiming to evaluate the independent association between serum Lp (a) and diabetic nephropathy in T2DM patients were identified by systematic search of PubMed and Embase databases. A random-effect model which incorporated the potential intra-study heterogeneity was used for the meta-analysis.ResultsEleven observational studies with 9304 T2DM patients were included. Results showed that compared to those with the lowest Lp (a), patients with the highest Lp (a) level had higher odds of diabetic nephropathy (adjusted odds ratio [OR]: 1.63, 95% confidence interval [CI]: 1.25–2.14, I2 = 54%, P &lt; 0.001). Meta-analysis of studies in which Lp (a) was presented as continuous variables showed consistent result (adjusted OR: 1.13 for 1 mg/dl increment of Lp (a), 95% CI: 1.03–1.24, I2 = 36%, P = 0.008). Subgroup analyses showed that study characteristics such as definitions of diabetic nephropathy and study design did not significantly affect the association (P for subgroup difference all &gt; 0.05).ConclusionsHigher serum Lp (a) in patients with T2DM is independently associated with higher odds of diabetic nephropathy. Large scale prospective cohort studies are needed to validate this finding. Moreover, the potential influence of Lp (a) lowering on renal function in T2DM patients may be further investigated.

scholarly journals Dietary fat and cholesterol and risk of diabetes in older adults

2018 ◽  
Vol 5 (7) ◽  
pp. 2610
Author(s):  
Ahmad Alqadheb ◽  
Noor Alsalman ◽  
Alaa Noor Elahi ◽  
Mohammed Alobaidan ◽  
Sarah Shams ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Older Adults ◽  
Dietary Fat ◽  
Meta Analysis ◽  
Random Effect Model ◽  
Cochrane Central Register ◽  
Egg Consumption ◽  
Effect Model

Type 2 diabetes is a major global public health issue, and the rapid increase in prevalence over the past decades is expected to continue. The present analysis aimed to investigate the relation between egg consumption and type 2 diabetes risk in older adults. We conducted this meta-analysis using a comprehensive search of MEDLINE, PubMed, EMBASE, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Trials till 01 February 2018 for prospective observational studies that assessed the relationship of the dietary fat and cholesterol and risk of diabetes in older adults. We identified 15 prospective studies that could be included in the meta-analysis. When comparing the highest with the lowest category of egg intake, pooled multivariate RRs of incident diabetes mellitus were 1.25 (95% CI: 1.13, 1.44) using a fixed-effect model and 1.12 (95% CI: 1.01, 1.56) using a random-effect model. There was evidence for heterogeneity (I2=75.8%, p<0.001). Our meta-analysis shows no relation between infrequent egg consumption and diabetes mellitus risk but suggests a modest elevated risk of diabetes mellitus with ≥3 eggs/wk that is restricted to US studies.

scholarly journals Relationship between air pollutants and risk of diabetes:a cohort study based meta-analysis

2019 ◽  
Author(s):  
Patamu Mohemaiti ◽  
Aidibai Simayi ◽  
Xiao Xiao Qin ◽  
Aizhatiguli Kadeer
Keyword(s):  
Air Pollutants ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
China National Knowledge Infrastructure ◽  
Knowledge Infrastructure ◽  
Effect Model ◽  
And Control

Abstract Background: To investigate the effects of air pollutants on the incidence of diabetes, and to provide reliable evidence for the prevention and control of diabetes.Method: Electronic databases of PubMed, Embase, Web of Science, Wanfang Digital Periodicals (WANFANG), WeiPu, China National Knowledge Infrastructure (CNKI), Springer, and Ovid were searched. RevMan5.3 software was used for meta analysis of the literature included in this study, I2 was used to measure the heterogeneity of the research contents of the included literature, and fixed effect model or random effect model was used for combined analysis of the overall incidence of diabetes and the incidence of diabetes under different air pollutants.Result: A total of 22 articles with high overall quality were included in this study, including 2703882 subjects and 535190 patients with diabetes.Pooled effect of the studies was determined using relative risk(RR). PM10 (RR=1.00; 95%CI:0.99-1.02, P=0.61), PM2.5 (RR=1.02 ; 95%CI:1.01-1.04, P=0.01), NOX (RR=1.00; 95%CI:1.00-1.01, P=0.006), NO2 (RR=1.00; 95%CI:1.00-1.01, P=0.01), O3 (RR=1.00; 95%CI:0.99-1.01, P=0.99). No correlation was found between PM10, NO2, O3 and the risk of type 2 diabetes. The risk of diabetes increased by 1% in people exposed to total air pollutants, increased by 2% in people exposed to PM2.5, and increased by 1% in people exposed to NOX.Conclusion: Results of this paper showed that air pollutants are weakly positively correlated with the risk of diabetes. As to the other influencing factors should be further studied.

scholarly journals Towards a MicroRNAs-Based Biomarker Panel for AIS: A Meta-Analysis

2021 ◽  
Author(s):  
Nadia Alejandra Rivero-Segura ◽  
Juan Carlos Gomez-Verjan ◽  
Ricardo. Mathn Ramírez-Aldana
Keyword(s):  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Biomarker Panel ◽  
Effect Model ◽  
Prisma Statement ◽  
Causes Of Mortality ◽  
Patient’S Outcome ◽  
Structural Networks

Background: Acute ischemic stroke is among the main causes of mortality worldwide; a rapid and opportune diagnosis is crucial to improve a patient's outcome. MicroRNAs are quite useful for a rapid and accurate diagnosis.Methods: We perform both structural networks approach and a meta-analysis (using a random-effect model to evaluate the heterogeneity and risk bias, according to the PRISMA statement) to analyze the feasibility to develop a microRNA-based biomarker panel for an opportune AIS diagnosis. Results: Structural networks identify a set of eight miRNAs (miR-16, miR-124-3p, miR-484, miR-15a, miR-4454, miR-107, miR-125b-5p and miR-320b) as preliminary microRNA-based biomarker panel, from these only three microRNAs are significantly associated with the main risk factors of AIS, (miR-107: hypertension, 95% CI 9.74-53.24 p&lt;0.0001, type 2 Diabetes mellitus, 95% CI 2.18-19.26); p=0.0008; miR-16 hypertension, 95% CI 1.26-3.56 p=0.0046, smoking, 95% CI 1.07-3.54 p=0.0277; and miR-15a hypertension, 95% CI 1.26-3.56 p=0.0046; smoking, 95% CI 1.07-3.54 p=0.0277). However, the meta-analysis reveals that data is highly heterogeneous and biased; and only microRNAs isolated from plasma samples and further processed in microarrays are the most reliable to distinguish AIS patients.Conclusions: Together our results show that although there are some miRNAs that seem to be associated with AIS, we are still far to develop a miRNA-based biomarker for AIS diagnosis and it is necessary to harmonize the protocols, results and include more populations for further studies otherwise we will remain throwing punches in the dark.

scholarly journals Relation Between Cigarette Smoking and Sarcopenia: Meta-Analysis

2015 ◽  
pp. 419-426 ◽  
Author(s):  
M. STEFFL ◽  
R. W. BOHANNON ◽  
M. PETR ◽  
E. KOHLIKOVA ◽  
I. HOLMEROVA
Keyword(s):  
Risk Factor ◽  
Cigarette Smoking ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Fixed Effect Model ◽  
Fixed Effect ◽  
Effect Model ◽  
The Individual ◽  
The Relationship

Cigarette smoking is a risk factor for many diseases. It could be associated with sarcopenia. The aim of this meta-analysis was to determine whether smoking is an isolated risk factor for sarcopenia. We searched PubMed, Web of Science, EBSCO, and Science Direct for articles addressing the relationship between cigarette smoking and sarcopenia. A total of 12 studies containing information on 22,515 participants were included in this meta-analysis. Odds ratio (OR) was calculated for each study group and for all studies together. An OR was also calculated separately for each sex. We used a fixed-effect model in overall estimation and in males, because results of small studies were significantly different from the results of large studies in those cases and in females where the estimation showed only moderate heterogeneity we used a random-effect model. According to proposes of the Cochrane Handbook for Systematic Reviews. The resulting OR in the fixed-effect model was 1.12 (95 % CI 1.03-1.21), OR for each sex was in the fixed-effect model 1.20 (95 % CI 1.06-1.35) in males and in the random-effect model 1.21 (95 % CI 0.92-1.59) in females. The results of this meta-analysis indicate that cigarette smoking as an isolated factor may contribute to the development of sarcopenia. However, the results of the individual studies were largely inconsistent due to different approaches of measuring the main variables which affected the results.

scholarly journals Meta-analysis on prevalence of cardiovascular diseases in patients with type 2 diabetes mellitus in India

2021 ◽  
Vol 7 (7) ◽  
pp. 355
Author(s):  
Poongothai J. Sakthivel ◽  
Poornima P. ◽  
Anantha Jothi S.
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Diabetes Type 2 ◽  
Incidence Rates ◽  
Type 2 Dm

<p class="abstract">Among various types of diabetes, type 2 diabetes mellitus (DM) is the most common type constituting 90% of the diabetic population. Out of several complications, cardiovascular disease (CVD) is predominant which leads to mortality. Various studies have reported different incidence rates of CVD in patients with type 2 DM. Hence, this meta-analysis study is aimed at determining the prevalence of CVD in patients with type 2 DM in India. In this review, studies were extracted by searching databases from PubMed, ScienceDirect, Google Scholar and Web of Science published between 2001 and 2021. The data collected from the extracted studies were analysed using comprehensive meta-analysis software which employs random effect model to combine the studies.  17 studies reviled 21.1% (95% CI: 17.9-24.7%) prevalence of cardiovascular CVDs in patients with type 2 DM in India. It is evident from literature review that women with DM are more prone CVD. If it is instituted that CVD is a major risk factor for DM in India, suitable scheme should be followed to improve the status of DM patients and should be brought to the note of hospitals.</p>

scholarly journals The Effect of Physical Activity on Glycemic Variability in Patients With Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

2021 ◽  
Vol 12 ◽  
Author(s):  
Xingyun Zhu ◽  
Lina Zhao ◽  
Jing Chen ◽  
Chu Lin ◽  
Fang Lv ◽  
...  
Keyword(s):  
Physical Activity ◽  
Diabetes Mellitus ◽  
Systematic Review ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Glycemic Variability ◽  
Control Group ◽  
Effect Model ◽  
Patients With Diabetes

PurposeThe effect of physical activity on glycemic variability remains controversial. This meta-analysis aimed to assess the overall effect of physical activity treatment on glycemic variability in patients with diabetes.MethodsPubMed/MEDLINE, Embase, and Cochrane databases were searched for clinical trials that conducted in patients with type 1 diabetes mellitus and type 2 diabetes mellitus with reports of the mean amplitude of glycemic excursion (MAGE), time in range (TIR), time above range (TAR), or time below range (TBR). Eligible trials were analyzed by fixed-effect model, random effect model, and meta-regression analysis accordingly.ResultsIn total, thirteen trials were included. Compared with the control group, physical activity intervention was significantly associated with increased TIR (WMDs, 4.17%; 95% CI, 1.11 to 7.23%, P&lt;0.01), decreased MAGE (WMDs, -0.68 mmol/L; 95% CI, -1.01 to -0.36 mmol/L, P&lt;0.01) and decreased TAR (WMDs, -3.54%; 95% CI, -5.21 to -1.88%, P&lt;0.01) in patients with diabetes, but showed insignificant effects on TBR. Patients with higher baseline BMI levels was associated with a greater decrease in MAGE (β=-0.392, 95% CI: -0.710, -0.074), and patients with lower baseline HbA1c levels was associated with a greater increase in TBR during physical activities (β=-0.903, 95% CI: -1.550, -0.255).ConclusionPhysical activity was associated with significantly decreased glycemic variability in patients with diabetes. Patients with higher BMI might benefit more from physical activity therapy in terms of a lower MAGE. Hypoglycemia associated with physical activity treatment still warranted caution, especially in patients with intensive glycemic control.Systematic Review RegistrationPROSPERO [CRD42021259807].

scholarly journals Cardio-Cerebrovascular Disease is Associated With Severity and Mortality of COVID-19: A Systematic Review and Meta-Analysis

2020 ◽  
pp. 109980042095198 ◽  
Author(s):  
Jia-Ning Yu ◽  
Bing-Bing Wu ◽  
Jie Yang ◽  
Xiao-Ling Lei ◽  
Wang-Qin Shen
Keyword(s):  
Diabetes Mellitus ◽  
Cerebrovascular Disease ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Severe Illness ◽  
Significant Relation ◽  
Effect Model ◽  
The World ◽  
Funnel Plots

At present, COVID-19 is raging all over the world. Many comorbidities, such as diabetes mellitus (OR = 2.67, 95% CI = 1.91–3.74) and hypertension (OR = 2.3, 95% CI = 1.76–3.00), have been shown to worsen the patient’s condition. However, whether cardio-cerebrovascular disease will affect COVID-19 remains unclear. In this meta-analysis, we collected studies from PubMed, Wed of Science and CNKI (Chinese) to July 25, which reported COVID-19 patients with and without cardio-cerebrovascular disease as well as their severity and mortality. The random-effect model meta-analysis was used to analyze them and get overall odds ratios (OR) with 95% CIs. Funnel plots and the Begg’s and Egger’s test were used to assess publication bias. Thirty-one studies with 23,632 patients were finally included in the meta-analysis. The results showed an OR of 3.004 (95% CI = 2.097–4.303) for COVID-19 severity and an OR of 5.587 (95% CI = 2.810–11.112) for COVID-19 mortality. Compared with cardiovascular disease, the subgroup analysis indicated that cerebrovascular disease was more likely to increase the severity (OR = 3.400, 95% CI = 1.569–7.368) and mortality (OR = 23.477, 95% CI = 3.050–180.735) of COVID-19. Therefore, it can be inferred that cardio-cerebrovascular disease is associated with an increase in the risk of severe illness and death among COVID-19 patients. This meta-analysis showed that cardio-cerebrovascular disease has a significant relation with severe and death outcomes of COVID-19. Nurses should pay special attention to COVID-19 patients with the cardio-cerebrovascular disease.

scholarly journals Gestational Diabetes in Malaysia: A Systematic Review of Prevalence, Risk Factors and Outcomes

2021 ◽  
Vol 50 (8) ◽  
pp. 2367-2377
Author(s):  
Lieng Teng Cheong ◽  
Ken Yong Foo ◽  
Mun Lum Ka ◽  
Yung Toh Shen ◽  
Xuan Hii Chan ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Systematic Review ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Meta Analysis ◽  
Random Effect ◽  
Random Effect Model ◽  
Effect Model ◽  
International Data

Gestational diabetes mellitus (GDM) is glucose intolerance first diagnosed during pregnancy. In Malaysia, the prevalence, risk factors, and maternal/foetal outcomes vary somewhat among the local studies. In this systematic review of Malaysian studies, we synthesise relevant data from 13 journal articles (including 10,285 women with gestational diabetes). A meta-analysis of twelve datasets showed a prevalence of 21.5% (95% CI 17.3 to 25.9%, random effect model). Clinical factors in the mother found to increase her risk of GDM were consistent with international data. A meta-analysis of complications showed statistically significant increase for macrosomia (OR 3.08, 95% CI 1.77 to 5.36) but not for pre-eclampsia (OR 1.44, 95% CI 0.52 to 4.00) and caesarean delivery (OR 1.31, 95% CI 0.98 to 1.75). The high prevalence of gestational diabetes mellitus and documented adverse consequences support the need for universal screening of this condition in all pregnant women in Malaysia.

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